skysight-inc/HackerNews huggingface dataset:
> Eerke Boiten, Professor of Cyber Security at De Montfort University Leicester, explains his belief that current AI should not be used for serious applications.

> In my mind, all this puts even state-of-the-art current AI systems in a position where professional responsibility dictates the avoidance of them in any serious application.

> Current AI systems also have a role to play as components of larger systems in limited scopes where their potentially erroneous outputs can be reliably detected and managed, or in contexts such as weather prediction where we had always expected stochastic predictions rather than certainty.

I think it's important to note that:

- Boiten is a security expert, but doesn't have a background working in ML/AI

- He never defines what "serious application" means, but apparently systems that are designed to be tolerant of missed predictions are not "serious".

He seems to want to trust a system at the same level that he trusts a theorem proved with formal methods, etc.

I think the frustrating part of this article is that from a security perspective, he's probably right about his recommendations, but he seems off-base in the analysis that gets him there.

> Current AI systems have no internal structure that relates meaningfully to their functionality. They cannot be developed, or reused, as components.

Obviously AI systems do have internal structure, and there are re-usable components both at the system level (e.g. we pick an embedding, we populate some vector DB with contents using that embedding, and create a retrieval system that can be used in multiple ways). The architecture of models themselves also has components which are reused, and we make choices about when to keep them frozen versus when to retrain them. Any look at architecture diagrams in ML papers shows one level of these components.

> exponential increases of training data and effort will give us modest increases in impressive plausibility but no foundational increase in reliability.

I think really the problem is that we're fixated on mostly-solving an ever broader set of problems rather than solving the existing problems more reliably. There's plenty of results about ensembling and learning theory that give us a direction to increase increase reliability (by paying for more models of the same size), but we seem far more interested in seeing if we can most of the time solve problems at a higher level of sophistication. That's a choice that we're making. Similarly Boiten mentions the possibility of models with explicit confidences -- and there's been plenty of work on that but b/c there's a tradeoff with model size (i.e. do you want to spend your resources on a bigger model, or on explicitly representing variance around a smaller set number of parameters?) but people seem mostly uninterested.

I think there are real reasons to be concerned about the specific path we're on, but these aren't the good ones.
Urxvt causes(d) my laptop running Ubuntu to sporadically but spontaneously power cycle, presumably due to bugs in the graphics drivers. Iirc it happened under Nvidia and Intel.
My point is that if you use biological cells to drive the system, which already exhibit intelligent behaviors, you don't have to worry about any of these questions. The basic unit you are using is already intelligent, so it's a given that the full system will be intelligent. And not an approximation but the real thing.
Someone ported this to python. Besides, an llm ca easily port the code as the value is in the algorithms not the source code.
I think that would be a more valid argument if they ever cared about automating away jobs before. As it stands, anyone who was standing in the way of the glorious march of automation towards a post-scarcity future was called a luddite - right up until that automation started threatening their (material) class.

I mean, you don't have to look any further than the (justified) lack of sympathy to dockworkers just a few months ago: https://news.ycombinator.com/item?id=41704618

The solution is not, and never has been, to shack up with the capital-c Capitalists in defense of copyright. It's to push for a system where having your "work" automated away is a relief, not a death sentence.
I’ve heard some contractors intentionally license source code they provide in a way that it can’t be reused and if it can only if they provide it to you again, so the government basically pays for the same code over and over. Even if it’s highly reusable. Maybe this will help with that?
Haha, that is some wonderful nonsense.
is anyone working on wp killer?

Open source easy to manage software that can have you blogging in minutes?
Can they take the pictures?
Rethinking Spot Instances – How We Solved the Preemption Problem
This is just amazing. I tried out with my startup's repo and it was a blast. Shared with my community
Thanks, that worked. Apparently, the reload-config hotkey doesn't always work for certain changes. In this case, setting `gtk-titlebar = false` disabled the header bar -- only issue now is that there is no menu bar at all!
> Nobody has a right to an audience.

That's literally what copyright is
I knew that they worked this way, but the conciseness of the response and clean analogy to systems I know and work with all day was just very satisfying.

For example, there was probably still 10-20% of my mind that assumed that stubbornness and ignorance was the reason for things going slowly most of the time, but I'm re-evaluating that, even though I knew that delays and double-checking were inherent features of a business and process. Re-framing those delays as "evolved responses 100% of the time" rather than "10% of the mistrust, 10% ignorance, 10% .... " is just a more positive way of thinking about human-driven processes.
Just so that there isn’t any confusion what russia is all about:

https://youtu.be/_9olGWX-1eI?si=MS4--_WH96BEjiSN

Very appropriate in light of the topic.
They claim their mission is to ensure that AGI benefits all humanity. What a preposterous lie.

I remember asking myself when ChatGPT was launched: "why would any sane person massively deploy such a thing?"

It's the money and the power, stupid.

OpenAI doesn't have any mission. To have a mission means to serve a purpose. To serve means to have higher values than money and power. And yeah, there is a hierarchy of values. The closest statement I can accept is "we will try to get all of humanity addicted to our models, and we couldn't care less about the consequences".

Wanna know why they'll lose? Because they'll get addicted too.
> Would you say a screen capture of Microsoft Excel is also copyright infringement?

Yeah it is. However most uses of an Excel screenshot would probably be considered fair use, and Microsoft probably doesn't care for 99% of use cases.

If you look at Wikipedia's Excel article they have more details on the legal rationale behind their use of a screenshot [1]. It looks like Microsoft allows the use of product screenshots in certain cases as well.

I also took a quick look at an Excel textbook I had on my shelf and it specifically stated in the copyright notice that they had permission from Microsoft to publish the screenshots used within.

https://en.wikipedia.org/wiki/File:Microsoft_Excel.png
link please

Edit, found it myself: https://www.reddit.com/r/Accounting/comments/1hnhoxq/comment...
I’m finding it very challenging to clearly distinguish between users and customers as I refine my Startup Idea Canvas (https://www.notion.com/templates/startup-idea-canvas). For most large companies, this differentiation is rarely a significant concern. However, for most early-stage startups—especially software startups with SaaS or Open Core models—these groups often overlap but usually have distinct roles.

In Paul Graham's essay "Startups in 13 Sentences"(https://paulgraham.com/13sentences.html), the terms "user" (22 times) and "customer" (6 times) reflect his focus on prioritizing users in a startup's early stages. This suggests that solving real problems for users lays the foundation for success, while monetization (paying customers) typically follows after achieving "making something users want."

Some challenges I’m grappling with:

When is differentiation necessary? Should every canvas explicitly separate these groups, or are there cases where treating them as the same makes sense?
How can this be represented leanly without overcomplicating the canvas?
Is it a better practice to approach product-market fit in two steps: first making something users want, and then making something customers want to pay for?
I’d be grateful for any insights, advice, suggestions, guidance, or examples you can offer.

Thanks in advance!
You guys are lucky. I didn't even get an e-mail. I just found out I couldn't login and happened across the website. So what are the chances of getting any kind of refund for the services I paid for and will not receive?
Hiding another AI post... This is getting _so_ tiresome...
> build an anki like system

...or use Anki? Set a calendar reminder to open the app, then there's a similar notification area trigger as with emails
I do the same on my personal projects. Big over engineering projects for learning purposes :-)
Data-loss prevention company Cyberhaven hit by breach, statement says
OpenAI's "Structured Outputs" Are Useful
Demand letters are the easiest. Drag and drop police report and medical records. Tell it to draft a demand letter. For most things, there are only a handful critical pages in the medical records, so if the original pdf is too big, I’ll trim excess pages. I may also add my personal case notes.

I use a custom prompt to adjust the tone, but that’s about it.
Hinton is a complete banana. If anything, we'll do it without technology.
I think they called it Steam Deck to avoid confusion with their previous Steam Machines.
The blogging engine is easy. The collection of third party themes and plugins is the hard part; and nobody wants to do that.

The code quality for many of those themes and plugins is also what a FAANG engineer would describe as “abysmal,” an “affront to the industry,” a “I can’t believe people use this,” a “this should be illegal,” whatever epithet you want. Huge surprise, no backwards compatibility coming to anywhere else, anytime soon.

90% of computer code in this world is crap. Crap that seniors would berate or fire people for. We don’t all live in the FAANG bubble; WordPress sadly is the biggest sign of that. The world runs on crap code built on crap architectures, outside of a few niche companies in a few niche geographies who congregate on a few niche forums (like this one). If you’re in one of them, count your blessings. If you’re not, don’t despair, you’ll be a senior-equivalent on a global level in no time.
Yep. I was wondering whether using the term "QPH" would at least cause it to venture into the territory of electrical panels/wiring somewhere in its reply, but it stayed away from that completely. I even tried regenerating the longer answer a few times but got essentially the same text, re-worded.
AI Is Shattering Hope of a Net Zero Future [video]
> Non-profit is a deal between those founders and society.

Yes I get that but did OpenAI ever take any public donations from society? I don't think they did. It thought it was only funded by wealthy private donors.

>, it’s the pivoting that’s inherently dishonorable.

Would creating a new company (i.e. ClosedAI) that recruits OpenAI's employees and buys the intellectual property such that it leaves a "shell" of OpenAI be acceptable?

That's basically the roundabout thing Sam is trying to do now with a re-incorporated for-profit PBC that's not beholden to the 2015 non-profit organization ... except he's also trying to keep the strong branding of the existing "OpenAI" name instead of "ClosedAI".

The existing laws allow for non-profit 501c3 organizations to "convert" (scare quotes) to for-profit status by re-incorporating to a (new) for-profit company. That seems to be Sam's legal roadmap.

EDIT REPLY: They received benefits by dint of their status. If there were no such benefits

The main benefit is tax exemption but OpenAI never had profits to be taxed. Also to clarify, there's already a for-profit OpenAI Global LLC. That's the subsidiary company Microsoft invested in. It has the convoluted "capped profit" structure. Sam says he can't attract enough investors to that for-profit entity. Therefore, he wants to create another for-profit OpenAI company that doesn't have the convoluted ("bespoke" as he put it) self-imposed rules to be more attractive to new investors.

The 2 entities of non-profit and for-profit is like Mozilla Foundation + Mozilla Corporation.

[] https://www.google.com/search?q=conversion+of+501c3+to+for-p...
This is also why there was reluctance to shoot the balloon down until it had passed over the ocean. The enormous payload container was a definite threat to life and limb if shot down over a populated area, and most of the US has at least a token population.
VW breach exposes location of 800k electric vehicles
This is generally good advice, but is a recipe to get extra work owning the implementation of the proposal.
If he adds AI, can he make it fly?
Noah Gibbs ( codefolio) has passed away
Yeah, no, that looks awful. At least three times more complicated that just writing HTML
I think that AI output is transformative.

I think the training process constitutes commercial use.
I think it does represent a dead end, but not for the reasons presented in this article.

The real issue in my opinion is that we will hit practical limits with training data and computational resources well before AGI turns us all into paperclips, basically there is no "Moore's Law" for AI and we are already slowing down using existing models like GPT.

We are in the vertical scaling phase of AI model development, which is not sustainable long-term.

I discussed this further here for anyone interested: https://techleader.pro/a/658-There-is-no-Moore's-Law-for-AI-...
Installing OpenWrt on the Banana Pi BPI-R4 [video]
What actual widespread non-shareholder value has AI given us?
Thanks! Another important factor I find is weather the configurations is file based or menu based.
There are already dozens of blogging applications out there to have you blogging in minutes. Wordpress is so far beyond 'blogging' that there will never be a 'wp killer'.

It's used for ecommerce, employee management systems, LMS/education platforms, membership/login sites (affinity groups, etc).

Whether it should be used for those use cases - building on top of something that wasn't really designed to be explicitly supportive of any of those use cases - that's another question.

There will be - and are - dozens of 'wp killers' - ecommerce systems, blogging platforms, etc - that will cover specific use cases. But there won't likely be anything generic/flexible enough like wordpress any time soon. And that's probably an overall good thing, but that's also a different argument to make.
While interesting, this is a separate thought experiment with its own quirks. Sort of a strawman, since my argument is formulated differently and simply argues that AIs need to be more than brains in jars for them to be considered generally intelligent.

And that the only reason we think AIs can just be brains in jars is because many of the people developing them consider themselves as simply brains in jars.
Do you do personal tax returns in addition to business taxes as part of a package?
There is no indication that Mochi is using any modern spaced repetition algorithm like FSRS. Even FSRS has huge problems but its the best one that's fully deployed and well tested and it is way better than SM-2. The future of SRS involves integration of fMRI based findings about memory formation and knowledge tracing but that is at least 5-15 years out.
ghostty is sick, and the diagram seems accurate on a higher level
Wir wissen, wo dein Auto steht
Ask HN: Achieved Professional Goals but Feel Lost–What's Next?
Longtime Hacker News poster here. I wanted to share this from a throwaway account for obvious reasons.

I run a company that's doing well. If we sold today, I'd likely walk away with $3–4 million, and at 29, that would be life-changing money for me. But despite the success, I'm struggling as we grow. I feel stuck and, honestly, a bit hopeless.

For so long, my goal was to build something valuable and be successful. Now that I’m achieving it, I’m starting to realize I might have been chasing the wrong things. Along the way, I met someone who profoundly impacted my life, but we broke up for reasons outside of our control. I don’t know if we’ll ever find our way back to each other, or if she was simply meant to be a chapter in my story. Either way, her presence in my life made me start to question what truly matters.

I still have the drive to succeed, but I’m beginning to see that there’s more to life than just being "a founder." It feels like I’ve outgrown parts of my life, including some of my friendships, which now seem rooted in immaturity. The one thing I thought would bring me joy—building this company—has instead left me reflecting on the parts of my youth I missed out on. Ironically, it’s made me feel more lonely as I struggle to move past the person I used to be. Part of me even wants to just walk away.

I guess, in short: has anyone ever felt like they accomplished their professional goals only to realize they were focused on the wrong things? I don’t regret the choices I’ve made or the journey I’ve been on—I understand that life is about enjoying the journey, not just reaching the destination. But now, I find myself asking: what do I do next?

TL:DR, At 29, I’ve built a successful company, but I feel unfulfilled and unsure if I’ve been chasing the wrong goals. Has anyone else hit their professional targets and felt lost? What’s next?
They are just DIY cruise missiles really.
AD rocket, by design, inflicts catastrophic damage even on military aircraft that have far better survivability. Even 10K rounds per minute autocannon of the Pantsir would generate such a dense cloud of shrapnel it'd be difficult to mistake it for "birds", especially for the pilots.
It’s not at all, energy is a hard constraint to capability.

Human intelligence improved dramatically after we improved our ability to extract nutrients from food via cooking

https://www.scientificamerican.com/article/food-for-thought-...
OK, so you have your own definition of knowledge. Please share it.
I always thought OpenAI was for the benefit of humanity, not a profit-seeking entity.

OpenAI is certainly not "open" nowadays.
Dogs, if I recall correctly, have evolved alongside us and have specific adaptations to better bond with us. They have eyebrow muscles that wolves don't, and I think dogs have brain adaptations too.
This aircraft was trying to land so it likely had much lower altitude and speed than usual.
Are you meaning (for example) old radar equipment with generated profiles unable to distinguish between what more modern equipment could?
Interesting. I'm looking for a tool to analyze HN posts like this for ages. Kind of reverse engineering yourself.
I ought to ask my dead grandma to save a kg of co2.
Ask HN: What will your "life operating system" look like in 2025?
* What works so well that you plan to keep it unchanged?
* What do you plan to tweak? How and why?
* What do you plan to add? How and why?
* What do you plan to scrap? Why?
>If you have a decent connection, streaming is so, so much better

This, pretending otherwise is just silly. I can understand that people enjoy the ritual with things like vinyl, but no one enjoys flipping through DVDs or the like.
> My own answer is that while some human speech behavior is possibly generated by systems that function in a semantically equivalent way to current LLMs, human cognition is capable of tasks that LLMs cannot perform de novo even if they can give the illusion of doing so (primarily causal chain reasoning). Consequently, LLMs are not in any real sense equivalent to a human being, and using them as such is a mistake.

In the workplace, humans are ultimately a tool to achieve a goal. LLM's don't have to be equivalent to humans to replace a human - they just have to be able to achieve the goal that the human has. 'Human' cognition likely isn't required for a huge amount of the work humans do. Heck, AI probably isn't required to automate a lot of the work that humans do, but it will accelerate how much can be automated and reduce the cost of automation.

So it depends what we mean as 'use them as a human being' - we are using human beings to do tasks, be it solving a billing dispute for a customer, processing a customers insurance claim, or reading through legal discovery. These aren't intrinsically 'human' tasks.

So 2 - yes, I do believe that they operate in a way that makes them useful for tasks. LLM's just respond to text prompts, but those text prompts can do useful things that humans are currently doing.
Interesting question. This "feels" valid (as a native speaker) - the "that" or "if" is implicit - but not a rule I had ever identified before.

Looks like this may be called an "empty complementizer"; some more info here: https://en.wikipedia.org/wiki/Complementizer#Empty_complemen...
Indeed, even if you have a professional accountant do your taxes, you must still sign off on their work.

Detecting omissions or errors on prepared tax forms often requires knowledge of context missed by or not provided to the accountant.
No one breaks kayfabe
Sometimes a best-seller is selling for a good reason. sometimes.
Vouching for this because "induced demand" is frequently used a discussion-ender with regards to transportation, but deserves more consideration.

We should definitely be vigilant against building infrastructure people will not use, but opinions around roads are treated very differently than houses, rail lines, runways, etc. No one is saying: "If we build more houses, people would just fill them up."

I am also against large road building projects, but for an entirely different reason. There's a very good chance that within 10 years, self driving cars could 5x the throughput capacity of existing roads.
I'm interested in this, too! I've been mulling over the design of 3D puzzles from 2D, laser-cut MDF.
This appears to be the source of the stat: https://www.resumebuilder.com/3-in-10-companies-currently-ha...

TBH, this doesn't really pass the smell test to me. Most people here seem to find it morally abhorrent, so the idea that 70% of "hiring managers" would find it acceptable is surprising, especially since most of these will be line managers who probably were ICs not that long ago. Also it says 68% reported a positive impact on revenue, which doesn't make any sense.

Ultimately, this is first and foremost a piece of content marketing, so their incentive is to get the biggest response not to be the most accurate.
Not really. The point of it is considering whether physical experience creates knowledge that is impossible to get otherwise. Thats the argument you are making no? If Mary learns nothing new when seeing red for the first time an AI would also learn nothing new when seeing red for the first time.

> Do they know what a hot shower feels like?
They can describe it. But do they actually know? Have they experienced it

Is directly a knowledge argument
KAL 007 was shot down as a suspected spy plane in peacetime, not as a suspected attack weapon in war time.
What I like about foot is the heuristics governing text selection with the mouse. I find that more often than not, if I double click with the mouse on some text, what it ends up selecting is just the part I need.
I suspect the big AI companies try to adversarially train that out as it could be used to "jailbreak" their AI.

I wonder though, what would be considered a meaningful punishment/reward to an AI agent? More/less training compute? Web search rate limits? That assumes that what the AI "wants" is to increase its own intelligence.
Well, the fact that Lc0 gives a huge advantage to black in the fourth position (not that it actually figures out good moves XD) gives some hope. Possible that it is just a question of how long we train the AI.
Humans are just amazing.